TY - JOUR AU - Mönninghoff, Annette AU - Kramer, Jan Niklas AU - Hess, Alexander Jan AU - Ismailova, Kamila AU - Teepe, Gisbert W AU - Tudor Car, Lorainne AU - Müller-Riemenschneider, Falk AU - Kowatsch, Tobias PY - 2021 DA - 201/4/30 TI -移动健康体育活动干预的长期有效性:JO - J Med Internet Res SP - e26699 VL - 23 IS - 4kw - mHealth KW -体力活动KW -系统评价KW -元分析KW -手机AB -背景:移动健康(mHealth)干预可以增加体力活动(PA);然而，它们的长期影响还没有得到很好的理解。目的:本研究的主要目的是了解移动健康干预对PA的近期和长期影响。次要目的是探索潜在的效应调节因子。方法:根据Cochrane和PRISMA (Preferred Reporting Items for Systematic Reviews and meta - analysis)指南进行研究。我们在2020年7月搜索了PubMed、Cochrane图书馆、SCOPUS和psyinfo。合格的研究包括以PA为主要结果的成人移动健康干预的随机对照试验。合格的结果测量包括步行、中度至剧烈身体活动(MVPA)、总身体活动(TPA)和能量消耗。在报告中，我们提取了3个时间点的数据(即干预结束、随访≤6个月、随访>6个月)。 To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool. Results: Of the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence. Conclusions: mHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects. SN - 1438-8871 UR - //www.mybigtv.com/2021/4/e26699 UR - https://doi.org/10.2196/26699 UR - http://www.ncbi.nlm.nih.gov/pubmed/33811021 DO - 10.2196/26699 ID - info:doi/10.2196/26699 ER -